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gbm3: Generalized Boosted Models

Originally written by Greg Ridgeway between 1999-2003, added to by various authors, extensively updated and polished by James Hickey in 2016, survival models greatly improved by Terry Therneau in 2016, and currently maintained by Greg Ridgeway. Development is discussed at the gbm-dev Google Group.

gbm3 provides generalized boosted regression models with a newer API than the original gbm package. The package supports regression, classification, survival models, and learning-to-rank methods, with optional OpenMP parallelization in the core fitting code.

Documentation and vignettes are available at https://gbm-developers.github.io/gbm3/.

To install the development version from GitHub, first install remotes:

install.packages("remotes")

Then install gbm3:

remotes::install_github("gbm-developers/gbm3")

# or to build vignettes during installation
remotes::install_github("gbm-developers/gbm3", build_vignettes = TRUE, force = TRUE)

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Install

install.packages('gbm3')

Monthly Downloads

521

Version

3.0.2

License

GPL (>= 2)

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Maintainer

Ridgeway Greg

Last Published

July 13th, 2026

Functions in gbm3 (3.0.2)

plot.GBMFit

Marginal plots of fitted gbm objects
training_params

Training parameters
quantile_rug

Quantile rug plot
trees

Extract trees from GBMFit objects
relative_influence

Methods for estimating relative influence
plot.GBMTPerformance

Plot GBM performance details
summary.GBMFit

Summary of a GBMFit object
to_old_gbm

Convert GBMFit to previous gbm object
predict.GBMFit

Predict method for GBM Model Fits
predict.GBMCVFit

Predictions for CV fitted GBM models
gbmt_performance

Get performance details for gbm fit
pretty_gbm_tree

Print gbm tree components
print.GBMFit

Print model summary
available_distributions

Available Distributions
gbm.perf

GBMT Performance
gbmParallel

Control parallelization options
distribution_name

What is the distribution name used here?
gbm_dist

GBM Distribution
create_dist

Create distributions
gbmt_fit

GBMT fit
gbm_more

Perform additional boosting
calibrate_plot

Calibration plot
interact

Estimate the strength of interaction effects
baseline_hazard

Baseline hazard function
gbm3-package

Generalized Boosted Regression Models
gbm_object

Generalized Boosted Regression Model Object
perf_pairwise

Performance for pairwise
gbm.fit

Generalized Boosted Regression Modeling
permutation_relative_influence

Relative influence via permutation
iteration_error

Extract errors from GBMFit objects
gbmt

GBMT
gbm_roc_area

Compute Information Retrieval measures.